Figure REF  shows the 3D representation of the environments we recorded the data for testing our system.
To validate our system, we used real thermal recordings from the JPL Mars Yard. The data was recorded from the industrial version of the FLIR Boson camera with a lens providing a 95-deg field of view (FOV). It generates 640 x 512 images in the \(7.5 {\mu }m\)  - \(13.5 {\mu }m\)  longwave infrared spectral range, with a thermal sensitivity under \(40 mK\)  and an 8-ms time constant. The camera was calibrated using as a target a circle grid pattern laminated over a Gatorfoam board left for 5 minutes in the sun, then the Kalibr toolbox [1]} was used to find the calibration parameters. The IMU used was the ICM20608 on-board the Pixhawk mini. This dataset is the same as the collection used for the work by Delaune et al. [2]}. We merged two Robot Operating System (ROS) bag files where two UAVs fly two squared trajectories with different altitudes, over the JPL Mars Yard for almost \(10 m\) , Figure REF  illustrates the two drones trajectories with their estimates. The data is collected with a five-minute distance in time. Therefore, we can rely on the assumption that the thermal fingerprint of the objects does not drastically change over time.
The results of our system compared against the baseline that is the standard xVIO implementation are reported in Table REF . We used the RPG trajectory evaluator tool [3]} to compute the Absolute Trajectory Error between the ground-truth and the estimates. The collaborative setup with photometric calibrated thermal images outperforms the standard xVIO by 12.26 and 46.12.
